Max-Stable Survival Copulas under Dependent Censoring: Sharp Identification and Efficient Inference
Abstract
We study dependent censoring within a generalized Cox first-hitting-time. framework based on compensator reductions. In the genuinely dependent case, we show that max-stability of the associated survival copula is equivalent to a common operational clock, leading to a nonparametric Marshall Olkin family. We establish sharp identification results under complete and binary observation schemes. Under binary observations, the common clock and event loading are point identified, whereas the censoring loading and the associated latent survival and dependence structures are only partially identified. We develop nonparametric estimation and inference for the identifiable components, derive an efficient restricted estimator, and propose an observable test of max-stable compatibility. Simulations and a real-data application illustrate the practical implications of the identification and efficiency results.
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BibTeX
@misc{gueye2026maxstable,
title = {{Max-Stable Survival Copulas under Dependent Censoring: Sharp Identification and Efficient Inference}},
author = {Djibril Gueye and Salima Helali and Modou Wade},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2608.28867},
eprint = {2608.28867},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.28867},
}
RIS
TY - UNPB
TI - Max-Stable Survival Copulas under Dependent Censoring: Sharp Identification and Efficient Inference
AU - Djibril Gueye
AU - Salima Helali
AU - Modou Wade
PY - 2026
DA - 2026/08/28
PB - arXiv
DO - 10.48550/arxiv.2608.28867
UR - https://arxiv.org/abs/2608.28867
AB - We study dependent censoring within a generalized Cox first-hitting-time. framework based on compensator reductions. In the genuinely dependent case, we show that max-stability of the associated survival copula is equivalent to a common operational clock, leading to a nonparametric Marshall Olkin family. We establish sharp identification results under complete and binary observation schemes. Under binary observations, the common clock and event loading are point identified, whereas the censoring loading and the associated latent survival and dependence structures are only partially identified. We develop nonparametric estimation and inference for the identifiable components, derive an efficient restricted estimator, and propose an observable test of max-stable compatibility. Simulations and a real-data application illustrate the practical implications of the identification and efficiency results.
ER -